{"title":"An Overview on Detecting Digital Image Splicing","authors":"Mohammed S. Khazaal, M. Kherallah, F. Charfi","doi":"10.1109/ACIT57182.2022.9994194","DOIUrl":null,"url":null,"abstract":"In today's society, digital images increasingly predominate as a source of information. However, they are easily modifiable with accessible image editing software. An image forgery technique that is frequently used is splicing. It involves combining two or more separate images to produce a merged image that differs greatly from the source image. Image splicing detection is crucial to digital forensics; hence it has recently drawn more attention. We present a comprehensive analysis of the research on several image splicing detection technologies. In the literature, a variety of methods utilizing machine and deep learning to detect image splicing have been suggested. The investigation carried out in this paper may assist the researcher in better comprehending the benefits and uses of the image splicing detection technologies already in use and in the development of more effective algorithms for detection.","PeriodicalId":256713,"journal":{"name":"2022 International Arab Conference on Information Technology (ACIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Arab Conference on Information Technology (ACIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACIT57182.2022.9994194","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In today's society, digital images increasingly predominate as a source of information. However, they are easily modifiable with accessible image editing software. An image forgery technique that is frequently used is splicing. It involves combining two or more separate images to produce a merged image that differs greatly from the source image. Image splicing detection is crucial to digital forensics; hence it has recently drawn more attention. We present a comprehensive analysis of the research on several image splicing detection technologies. In the literature, a variety of methods utilizing machine and deep learning to detect image splicing have been suggested. The investigation carried out in this paper may assist the researcher in better comprehending the benefits and uses of the image splicing detection technologies already in use and in the development of more effective algorithms for detection.